Article ID Journal Published Year Pages File Type
388588 Expert Systems with Applications 2007 12 Pages PDF
Abstract

One of the significant research problems in multivariate analysis is the selection of a subset of input variables that can predict the desired output with an acceptable level of accuracy. This goal is attained through the elimination of the variables that produce noise or, are strictly correlated with other already selected variables. Feature subset selection (selection of the input variables) is important in correlation analysis and in the field of classification and modeling. This paper presents a hybrid method based on ant colony optimization and artificial neural networks (ANNs) to address feature selection. The proposed hybrid model is demonstrated using data sets from the domain of medical diagnosis, yielding promising results.

Related Topics
Physical Sciences and Engineering Computer Science Artificial Intelligence
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